AdvancedMH.DensityModel
— TypeDensityModel{F} <: AbstractModel
DensityModel
wraps around a self-contained log-liklihood function logdensity
.
Example:
l(x) = logpdf(Normal(), x)
-DensityModel(l)
diff --git a/previews/PR92/.documenter-siteinfo.json b/previews/PR92/.documenter-siteinfo.json index 1b382b6..51efe59 100644 --- a/previews/PR92/.documenter-siteinfo.json +++ b/previews/PR92/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-10-27T09:38:12","documenter_version":"1.1.2"}} \ No newline at end of file +{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-10-27T09:38:26","documenter_version":"1.1.2"}} \ No newline at end of file diff --git a/previews/PR92/api/index.html b/previews/PR92/api/index.html index bee626a..4a0dd9d 100644 --- a/previews/PR92/api/index.html +++ b/previews/PR92/api/index.html @@ -5,5 +5,5 @@ Other allowed proposals are
p1 = StaticProposal(Normal(0,1)) p2 = StaticProposal([Normal(0,1), InverseGamma(2,3)]) p3 = StaticProposal((a=Normal(0,1), b=InverseGamma(2,3))) p4 = StaticProposal((x=1.0) -> Normal(x, 1))
The sampler is constructed using
-
julia spl = MetropolisHastings(proposal) ```
When using MetropolisHastings
with the function sample
, the following keyword arguments are allowed:
initial_params
defines the initial parameterization for your model. Ifnone is given, the initial parameters will be drawn from the sampler's proposals.
param_names
is a vector of strings to be assigned to parameters. This is onlyused if chain_type=Chains
.
chain_type
is the type of chain you would like returned to you. Supportedtypes are chain_type=Chains
if MCMCChains
is imported, or chain_type=StructArray
if StructArrays
is imported.
AdvancedMH.DensityModel
— TypeDensityModel{F} <: AbstractModel
DensityModel
wraps around a self-contained log-liklihood function logdensity
.
Example:
l(x) = logpdf(Normal(), x)
-DensityModel(l)
Settings
This document was generated with Documenter.jl version 1.1.2 on Friday 27 October 2023. Using Julia version 1.9.3.